Finding Lines under Bounded Error
Thomas M. Breuel
IDIAP
C.P. 609, 1920 Martigny, Switzerland
tmb@idiap.ch
A new algorithm for finding straight lines in images under a bounded
error model is described. The algorithm is based on a hierarchical
and adaptive subdivision of the space of line parameters. It measures
errors in image space and thereby guarantees that no solution
satisfying the given error bounds will be lost. The algorithm can
find interpretations of all the lines in the image that satisfy the
constraint that each image feature supports at most one line
hypothesis. It can be extended to compute efficiently the maxima of
the probabilistic Hough transform and the generalized Hough transform
under a variety of statistical error models.